Comparing Coefficients of Nonlinear Multivariate Regression Models Between Equations

Christoph Kern, Petra Stein


The present study discusses the usage of non-linear constraints in regression models with multiple categorical outcomes. With this approach, effect differences between equations are made accessible to statistical tests while potential differences in residual variation are explicitly taken into account. In this context, it can be shown that the techniques reviewed by Williams (2010) are conjointly equivalent to the specification of non-linear constraints in multivariate regression models. However, the application of non-linear constraints extends these approaches into a structural equation modeling framework, which allows the researcher to address a broader range of research questions.


non-linear constraints; structural equation modeling; effect comparison

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